{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T08:17:27Z","timestamp":1781684247695,"version":"3.54.5"},"reference-count":117,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T00:00:00Z","timestamp":1660608000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Foundation for Science and Technology, I.P. (Portuguese Foundation for Science and Technology)","award":["UIDB\/05064\/2020"],"award-info":[{"award-number":["UIDB\/05064\/2020"]}]},{"name":"Foundation for Science and Technology, I.P. (Portuguese Foundation for Science and Technology)","award":["UIDB\/04111\/2020"],"award-info":[{"award-number":["UIDB\/04111\/2020"]}]},{"name":"Foundation for Science and Technology, I.P. (Portuguese Foundation for Science and Technology)","award":["COFAC\/ILIND\/COPELABS\/3\/2020"],"award-info":[{"award-number":["COFAC\/ILIND\/COPELABS\/3\/2020"]}]},{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization","award":["UIDB\/05064\/2020"],"award-info":[{"award-number":["UIDB\/05064\/2020"]}]},{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization","award":["UIDB\/04111\/2020"],"award-info":[{"award-number":["UIDB\/04111\/2020"]}]},{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization","award":["COFAC\/ILIND\/COPELABS\/3\/2020"],"award-info":[{"award-number":["COFAC\/ILIND\/COPELABS\/3\/2020"]}]},{"name":"ILIND\u2014Lusophone Institute of Investigation and Development","award":["UIDB\/05064\/2020"],"award-info":[{"award-number":["UIDB\/05064\/2020"]}]},{"name":"ILIND\u2014Lusophone Institute of Investigation and Development","award":["UIDB\/04111\/2020"],"award-info":[{"award-number":["UIDB\/04111\/2020"]}]},{"name":"ILIND\u2014Lusophone Institute of Investigation and Development","award":["COFAC\/ILIND\/COPELABS\/3\/2020"],"award-info":[{"award-number":["COFAC\/ILIND\/COPELABS\/3\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To improve the monitoring of the electrical power grid, it is necessary to evaluate the influence of contamination in relation to leakage current and its progression to a disruptive discharge. In this paper, insulators were tested in a saline chamber to simulate the increase of salt contamination on their surface. From the time series forecasting of the leakage current, it is possible to evaluate the development of the fault before a flashover occurs. In this paper, for a complete evaluation, the long short-term memory (LSTM), group method of data handling (GMDH), adaptive neuro-fuzzy inference system (ANFIS), bootstrap aggregation (bagging), sequential learning (boosting), random subspace, and stacked generalization (stacking) ensemble learning models are analyzed. From the results of the best structure of the models, the hyperparameters are evaluated and the wavelet transform is used to obtain an enhanced model. The contribution of this paper is related to the improvement of well-established models using the wavelet transform, thus obtaining hybrid models that can be used for several applications. The results showed that using the wavelet transform leads to an improvement in all the used models, especially the wavelet ANFIS model, which had a mean RMSE of 1.58 \u00d710\u22123, being the model that had the best result. Furthermore, the results for the standard deviation were 2.18 \u00d710\u221219, showing that the model is stable and robust for the application under study. Future work can be performed using other components of the distribution power grid susceptible to contamination because they are installed outdoors.<\/jats:p>","DOI":"10.3390\/s22166121","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T03:15:27Z","timestamp":1660706127000},"page":"6121","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models"],"prefix":"10.3390","volume":"22","author":[{"given":"Nemesio Fava","family":"Sopelsa Neto","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Regional University of Blumenau, Rua S\u00e3o Paulo 3250, Blumenau 89030-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3723-616X","authenticated-orcid":false,"given":"Stefano Frizzo","family":"Stefenon","sequence":"additional","affiliation":[{"name":"Fondazione Bruno Kessler, Via Sommarive 18, 38123 Trento, Italy"},{"name":"Department of Mathematics, Informatics and Physical Sciences, University of Udine, Via delle Scienze 206, 33100 Udine, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0569-2416","authenticated-orcid":false,"given":"Luiz Henrique","family":"Meyer","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Regional University of Blumenau, Rua S\u00e3o Paulo 3250, Blumenau 89030-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2862-3053","authenticated-orcid":false,"given":"Ra\u00fal Garc\u00eda","family":"Ovejero","sequence":"additional","affiliation":[{"name":"Expert Systems and Applications Laboratory, E.T.S.I.I. of B\u00e9jar, Universidad de Salamanca, 37700 Salamanca, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0446-9271","authenticated-orcid":false,"given":"Valderi Reis Quietinho","family":"Leithardt","sequence":"additional","affiliation":[{"name":"COPELABS, Lus\u00f3fona University of Humanities and Technologies, Campo Grande 376, 1749-024 Lisboa, Portugal"},{"name":"VALORIZA, Research Center for Endogenous Resources Valorization, Instituto Polit\u00e9cnico de Portalegre, 7300-555 Portalegre, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"75586","DOI":"10.1109\/ACCESS.2020.2987705","article-title":"Analysis of Thermal Sensitivity by High Voltage Insulator Materials","volume":"8","author":"Kim","year":"2020","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1049\/gtd2.12425","article-title":"Optimal design of electrical power distribution grid spacers using finite element method","volume":"16","author":"Stefenon","year":"2022","journal-title":"IET Gener. 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